• DocumentCode
    3672453
  • Title

    Saturation-preserving specular reflection separation

  • Author

    Yuanliu Liu; Zejian Yuan; Nanning Zheng; Yang Wu

  • Author_Institution
    Institute of Artificial Intelligence and Robotics, Xi´an Jiaotong University, China
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    3725
  • Lastpage
    3733
  • Abstract
    Specular reflection generally decreases the saturation of surface colors, which will be possibly confused with other colors that have the same hue but lower saturation. Traditional methods for specular reflection separation suffer this problem of hue-saturation ambiguity, producing over-saturated specular-free images quite often. We proposed a two-step approach to solve this problem. In the first step, we produce an over-saturated specular-free image by global chromaticity propagation from specular-free pixels to highlighted ones. Then we recover the saturation based on priors of the piecewise constancy of diffuse chromaticity as well as the spatial sparsity and smoothness of specular reflection. We achieve this through increasing the achromatic component of diffuse chromaticity, while the magnitudes of increments are determined by linear programming under the constraints derived from the priors. Experiments on both laboratory and natural images show that our method can separate the specular reflection while preserving the saturation of the underlying surface colors.
  • Keywords
    "Image color analysis","Colored noise","Lighting","Linear programming","Rough surfaces","Surface roughness"
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2015.7298996
  • Filename
    7298996